Triple
T14601307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catacombs of Paris |
E342710
|
entity |
| Predicate | publiclyAccessibleSectionLength |
P61783
|
FINISHED |
| Object | about 1.5 kilometers |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: about 1.5 kilometers | Statement: [Catacombs of Paris, publiclyAccessibleSectionLength, about 1.5 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publiclyAccessibleSectionLength Context triple: [Catacombs of Paris, publiclyAccessibleSectionLength, about 1.5 kilometers]
-
A.
hasSectionLength
chosen
Indicates that an entity is associated with a specific length value for one of its sections.
-
B.
extensionLength
Indicates the length or magnitude of an extension from a reference point or base object.
-
C.
borderSectionLength
Indicates the measured length of a specific segment of a shared border between two geographic or administrative areas.
-
D.
isPubliclyAccessible
Indicates that the referenced entity can be accessed or used by the general public without special permissions or restrictions.
-
E.
sectionCountApproximate
Indicates that the number of sections associated with an entity is known only approximately rather than as an exact count.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb438748081908020ce04b869866a |
completed | April 14, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69de656a953481909a4645b004c40de7 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:25 a.m.